POLYMARKET · PREDICTION MARKET · WHAT IRANIAN DEMANDS WILL TRUMP AGREE TO BY JUNE 30?
Will Trump agree to unfreeze Iranian assets by June 30?
50.0¢
50.0¢
▸ Advanced metrics · M2M bundle
polymarket · will-trump-agree-to-unfreeze-iranian-assets-by-june-30 · fresh · feed 16s old24h sparkline · 60 pts▼ —
realized vol (ann.)
421.61%
max drawdown
20.56%
sharpe
—
ulcer index
8.95%
RMS drawdown
pain index
6.90%
mean drawdown
mod. VaR 95%
0.00%
Cornish-Fisher
martin ratio
—
ret / ulcer
CDaR 95%
18.07%
cond. drawdown
gain/pain
0.85
Σgain / Σ|loss|
sterling
—
ret / CDaR
omega (θ=0)
0.85
upside/downside
roll spread
0.7 bps
implied (price-only)
bars used
2000
store
spread
—
24h Δ
—
flow lean
—
carry
flat
signalNEUTRALconfidence 20%
Same bundle via M2M API:
/api/m2m/pm-will-trump-agree-to-unfreeze-iranian-assets-by-june-30/bundle · venue execution: polymarket →LIVEPOLL0SRCWARMING⏱--:--:-- UTCNEXT8.0sUP0s--:--HIST
▶ STREAMING·HYPERLIQUID·POLYMARKET·0 POLLS·SRC WARMING·UPTIME 0s·NEXT POLL 8.0s·CC0 OPEN DATA·HYPO.MARKETS·▶ STREAMING·HYPERLIQUID·POLYMARKET·0 POLLS·SRC WARMING·UPTIME 0s·NEXT POLL 8.0s·CC0 OPEN DATA·HYPO.MARKETS·
YES · live
50.0¢
NO · live
50.0¢
25 ticks · last 47.50¢
Σ 100.00% · fair
Σ-sides total = 100.00% (tight rounding)
H(p) entropy = 1.000 / 1.00 bits (100%) · max uncertainty (~50/50)
YES50.0%50.0¢2.00×▬ +0.00pp
NO50.0%50.0¢2.00×▬ +0.00pp
Σ 100.00% · arb gap 0.00pp
Σ 7700bp moved · peak 1100bp · n=24 ticks
16.0s
50.00¢ (50.00%)
50.00¢ (50.00%)
100.00%
0.000pp
$62.4k
$46.7k
25 ticks (live)
§1 · 24h price history (YES + NO tokens)
25 YES observations from clob.polymarket.com · last 47.50¢
25 NO observations from clob.polymarket.com · last 52.50¢
§2 · Distribution of Δp
n=24
reference line = identity (perfect normality). Heavy upper-right tail = fat positive tail.
§3 · Sample moments
SAMPLE MOMENTS · N=25APPROXIMATELY NORMAL · WELL-BEHAVED
FIVE-NUMBER SUMMARY · BOX PLOT
SKEWNESS · G₁-0.316approximately symmetric
−3−10+1+3
EXCESS KURTOSIS · G₂-0.486mesokurtic · normal-like
−30+2+4+6
μ = mean YES probability · σ = standard deviation · 95% CI = μ ± 1.96·SE. Skew/kurt diagnose departure from normality.
§5 · Time-series structure
TIME-SERIES STRUCTUREREGIME: MEAN-REVERTING · ADF rejects unit root
HURST EXPONENT [0, 1]
H = 0.906STRONGLY PERSISTENT
0
anti-persistent0.45
mean-reverting0.5
random walk0.55
persistent1
strongly trending
anti-persistent0.45
mean-reverting0.5
random walk0.55
persistent1
strongly trending
AUTOCORRELATION FUNCTION · ρ(k) for k=1..5
OLS TREND · t-STAT · [-5, +5]
−5 reject−1.960 retain H₀+1.96+5 reject
ρ(k) = lag-k sample autocorrelation · H = R/S Hurst exponent · t = OLS-trend t-statistic. Significance bands at ±2/√n approximate the 95% white-noise envelope. α=0.05 critical |t|=1.96; α=0.01 |t|=2.58.
§6 · Microstructure
MICROSTRUCTURE · MARKET QUALITYPERFECT · ARB-FREE Σ=100.00%
TWO-SIDED PRICING
50.00¢
50.00¢
Σ-SIDES ARBITRAGE TEST
Σ = 100.00% · |1 − Σ| = 0.000pp
24H ACTIVITY · LIQUIDITY
Σ-sides = YES + NO implied probabilities. Perfect arb-free Σ = 100%. |1−Σ| > 2pp suggests synthetic outright arbitrage.
§7 · Position sizing & edge analysis
FAIR MARKET · no edge
Probability scale (YES)
Implied decimal odds
YES2.00×(50¢)NO2.00×(50¢)
Kelly bet-size (% of bankroll) K* = 0.00%
Entropy H(p̂) = 1.000 bits (100% of max) · maximum uncertainty (~50/50)
Σ-sides = 100.00% · |1 − Σ| = 0.00pp · tight cross-venue rounding
K* full = (b·p − q)/b · ½K and ¼K are conservative fractions of the full-Kelly bet. Entropy in bits — log₂(2)=1 is maximum uncertainty for a binary market.
§8 · Time decay & θ projection
⏱ URGENCY · DISTANTresolves 2026-06-30 00:00 UTC
15days
12hrs
50min
YES →$1.00
NO →$0.00
current: $0.5000 · expected return per side: $0.50 on YES hit · $0.50 on NO hit
Theta progression · θ ∝ σ / √t_remainingθ_now = 18.602 pp/day
now15.53d left18.602 pp/day×1.00
−25%11.65d left21.480 pp/day×1.15
−50%7.77d left26.307 pp/day×1.41
−75%3.88d left37.204 pp/day×2.00
−90%1.55d left58.825 pp/day×3.16
θ approximation: σ/√T (expected daily move magnitude). The cone shows ±√(p̂(1−p̂)) widening as time decays, funneling to {0, 1} at resolution. Theta accelerates as √(t_left)→0.
§9 · Hourly return heatmap
8 up bars · 13 down · best 7.50% · worst -11.00% · typical |Δ| 3.208%
§10 · Equity curve & underwater drawdown
final equity 0.8926 (-10.74%) · max DD -13.67% · time-under-water 23/25 bars
§11 · Rolling-window statistics (w = 6 bars)
latest -15.330 · range [-89.24, 38.53] · μ -13.540 · positive Sharpe = excess-return-per-risk earned by buying-and-holding through this window
latest 380.95% · range [72.50%, 645.34%] · μ 342.58% · σ̂ scaled to annualised (×√8760)
latest -0.431 · |ρ| > 0.3 ⇒ regime with persistence (ρ > 0) or reversal (ρ < 0) · |ρ| ≤ 0.1 = consistent with random walk
§12 · Hypothesis tests (α = 0.05)
1 of 6 REJECT · mixed evidence1 reject·5 pass·α = 0.05
Jarque-Bera
FAIL TO REJECTnsH₀: Δp ~ Normal(μ, σ²)
STATISTIC
0.4419
p-VALUE (log scale)
0.8018
Ljung-Box(h=5)
FAIL TO REJECTnsH₀: No serial autocorrelation up to lag 5
STATISTIC
4.0746
p-VALUE (log scale)
0.5406
Dickey-Fuller (τ_μ)
REJECT H₀**H₀: p has a unit root (non-stationary)
STATISTIC
-3.6710
p-VALUE (log scale)
0.0049
Wald-Wolfowitz runs
FAIL TO REJECTnsH₀: Sign sequence of Δ is random
STATISTIC
0.0454
p-VALUE (log scale)
0.9638
KPSS (μ stationarity)
FAIL TO REJECTnsH₀: p IS level-stationary
STATISTIC
0.1588
p-VALUE (log scale)
0.4287
Variance ratio q=3
FAIL TO REJECTnsH₀: Δp is a random walk · VR = 1
STATISTIC
-1.2822
p-VALUE (log scale)
0.1998
Each row states an explicit null H₀, the test statistic, an approximated p-value, and the decision. REJECT means evidence against H₀. KPSS complements ADF (rejecting both ⇒ ambiguous; rejecting one ⇒ clean verdict).
§13 · Spectral analysis (DFT periodogram)
dominant period ≈ 6.00h (freq 0.167) · concentrates 26.5% of total energy · Σ|X̂|²/n = 2.488e-2
▸ Depth section using sovereign-store price series (2825 bars · effective 1752810 bars/year) — annualisation reflects native polling cadence, not upstream timeframes.
§14 · Honest position analytics
A binary-market analytics module framed in horizon time (days to resolution, not annualised). Estimators that need a model probability q as a first-class input (Kelly, KL divergence, Bayesian posterior, Mark-to-Market MC) only render when q is provided externally. Sweep an exploratory q at the interactive simulator →
§15 · Horizon returns
Horizon 15.5 d · σ/bar 0.327pp · expected |Δp| over horizon 6.31ppterminal variance p(1−p) = 0.2500 · n = 2825✓ n = 2825
μ per bar
+0.001pp
average Δp · drift
σ per bar
0.327pp
one-bar volatility · logit-free
Per-day movedaily
1.60pp
σ × √24
Per-horizon move16d
6.31pp
σ × √372.838225
Terminal variancebinary
0.2500
p(1−p) at resolution
Current pricep
50.0¢
latest snapshot
Note: annualised Sharpe/Sortino are omitted — they are not meaningful for a bounded fixed-horizon binary contract that snaps to {0, 1} at resolution.
Annualised metrics are intentionally omitted — they don't apply to bounded probability series that resolve at a fixed date.
§16 · Tail risk
VaR₉₅ 0.54pp · ES₉₅ 0.67pp · method parametric · drift-correcteddrift +0.001pp/bar · quantised: yes · median step 0.50pp · unique ratio 0.01✓ n = 2825
VaR 95%
0.54pp
1.645·σ (parametric) of Δp
ES 95%
0.67pp
mean of the tail
Max drawdown
20.6pp
peak 53.5¢ → trough 42.5¢
Median step
0.50pp
price bucket granularity
Price series is bucketed (cent grid). Empirical quantiles collapse to grid points — parametric N(0, σ²) used instead.
Empirical quantiles unless the price series is bucketed (PM cent grid), in which case parametric N(0, σ²) is used to avoid grid collapse.
§17 · Odds conversion
Implied probabilityP
50.0%
= price
Decimal oddsEU
2.000
total return per $1
AmericanUS
-100
risk $100 to win $100
FractionalUK
1.00 / 1
profit per $1 risked
Profit per $100stake
+$100.00
clean dollar framing
underdog (+)favorite (-)your price
Price → implied probability → decimal odds → American moneyline → fractional. Five views of the same number, plus the moneyline curve.
§18 · Binary entropy
Market entropyH(p)
1.000 bit
max 1.0 at p = 0.5
Your entropyH(q)
1.000 bit
Δ +0.000 bit vs market
Surprise · YES−log₂ p
1.00 bit
self-information
Surprise · NO−log₂(1−p)
1.00 bit
self-information
Market entropy only — model entropy requires an external q.
§19 · Model-dependent surfaces
External model required
The position-economics, Kelly, KL-divergence, Bayesian and Monte-Carlo surfaces require a model probability q as input — a number independent of the market price p.
The previous build defaulted q to a tape-momentum heuristic derived from p; that produces apparent edge that is structurally guaranteed to be small and is not a useful skill signal. The auto-derived path has been removed.
To explore these surfaces with a hypothetical q, open the interactive simulator and drag the MODEL P(YES) slider. To wire a real model, POST to the NOSTRADAMUS hook (TBD) or pass ?q=… on the simulator URL.
§∞ · Provenance & attestation
- Upstream (snapshot)
- gamma-api.polymarket.com
- Upstream (history)
- clob.polymarket.com
- YES token ID
21156921203468644956193993351150340626282049382890294631366123375763306943605- NO token ID
99888603392363486484408086839426612108324711143939711496894787635542726338226- Snapshot fetched
- 2026-06-14 11:09:26 UTC
- Snapshot age
- 16.0s
- History points
- 25 CLOB mids
- Page rendered
- 2026-06-14 11:09:42 UTC
- Storage policy
- no persistence — fetched on every request
- SHA-256 attestation
0f990357ed911fa6096a6a1ff7c44f7a9a1e082bcff66a7f72c2d0df82e5d8ba· deterministic hash of source snapshot- Open data licence
- CC0 / public domain
§∞-2 · Related markets · explore more
HL PREDGermany94.4¢HL PREDSpain90.4¢HL PREDUruguay66.6¢POLYMARKETWill Australia win the 2026 FIFA World Cup?0¢POLYMARKETWill Scotland win the 2026 FIFA World Cup?0¢POLYMARKETUS x Iran permanent peace deal by June 15, 2026?23¢HL PERPBTC-USD perpetual$64,490HL PERPETH-USD perpetual$1,672.9HL PERPHYPE-USD perpetual$60.73
Also see: /arb opportunities · RSS feed · more in What Iranian demands will Trump agree to by June 30?
Market depth
▸ live order book · Polymarket YESDepth within 1bp
$0
bid $0 · ask $0
Depth within 5bp
$0
bid $0 · ask $0
Depth within 10bp
$0
bid $0 · ask $0
Depth within 50bp
$0
bid $0 · ask $0
Mid price
0.475000
(best bid + best ask) / 2
Spread
210.5bp
(bestAsk − bestBid) / mid
Imbalance (whole book)
+0.138
bid-heavy
Imbalance (top-5)
+0.149
bid-heavy top-of-book
Slippage scenarios
▸ live book walk · Polymarket YESSimulating a market order at three notionals against the live book. Slippage = avg execution price vs. mid, in basis points. Worst fill = price of the deepest level touched. Live JSON: /api/asset/pm-will-trump-agree-to-unfreeze-iranian-assets-by-june-30/slippage?size=10000&side=buy
| Side | Notional | Avg fill | Slippage | Worst fill | Levels | Status |
|---|---|---|---|---|---|---|
| BUY | $1.00K | 0.532438 | 1209.22bp | 0.540000 | 5 | FILLED |
| BUY | $10.00K | 0.584134 | 2297.56bp | 0.630000 | 14 | FILLED |
| BUY | $100.00K | 0.842459 | 7735.98bp | 0.950000 | 36 | FILLED |
| SELL | $1.00K | 0.451683 | 490.89bp | 0.440000 | 4 | FILLED |
| SELL | $10.00K | 0.262211 | 4479.77bp | 0.160000 | 26 | FILLED |
| SELL | $100.00K | 0.071271 | 8499.55bp | 0.010000 | 41 | PARTIAL |
Risk metrics
▸ sovereign store · 2,825 barsperiods/year ≈ 1.75MRealized vol (annualised)
866.20%
σ per bar = 0.006543
Mean return (annualised)
4504.34%
μ per bar = 0.000026
Sharpe (rf=0)
5.20
annualised; risk-free assumed zero
Max drawdown
20.56%
peak 0.54 → trough 0.42 over 1852 bars
/api/asset/pm-will-trump-agree-to-unfreeze-iranian-assets-by-june-30/risk · same metrics, JSON